Interface Features.Payoffs

All Superinterfaces:

Features

All Known Subinterfaces:

Features.Static

All Known Implementing Classes:

ATBT, CDL, CDLP, CDLPQ, Centipede, CLabour, CSD, DemesTBT, EcoPGG, Moran, NetGames, RSP, scanCSD, simCDL, simCDLP, simCDLPQ, simMoran, simTBT, simTraits, TBT, Traits

Enclosing interface:

Features

public static interface Features.Payoffs
extends Features

Interface that all modules with frequency dependent fitness/payoffs should implement. The classical 2x2 games is an example, see TBT.

Author:

Christoph Hauert

Nested Class Summary

Nested classes/interfaces inherited from interface Features

Features.Groups, Features.Multispecies, Features.Pairs, Features.Payoffs, Features.Static

Method Summary

Modifier and Type	Method	Description
Map2Fitness	getMap2Fitness()	Gets the score/payoff to fitness map.
double	getMaxMonoPayoff()	Calculates and returns the maximum payoff/score of individuals in monomorphic populations.
double	getMaxPayoff()	Calculates and returns the maximum payoff/score of an individual.
double	getMinMonoPayoff()	Calculates and returns the minimum payoff/score of individuals in monomorphic populations.
double	getMinPayoff()	Calculates and returns the minimum payoff/score of an individual.
default boolean	isNeutral()	Checks whether dynamic is neutral, i.e.

Methods inherited from interface Features

getTitle, isMultispecies, isPairwise, isStatic

Method Details

getMinPayoff

double getMinPayoff()

Calculates and returns the minimum payoff/score of an individual. This value is important for converting payoffs/scores into probabilities, for scaling graphical output and some optimizations.

Returns:

the minimum payoff/score

See Also:

• Model.getMinScore(int)

getMaxPayoff

double getMaxPayoff()

Calculates and returns the maximum payoff/score of an individual. This value is important for converting payoffs/scores into probabilities, for scaling graphical output and some optimizations.

Returns:

the maximum payoff/score

See Also:

• Model.getMaxScore(int)

isNeutral

default boolean isNeutral()

Checks whether dynamic is neutral, i.e. no selection acting on the different traits.

Returns:

true if all payoffs identical

getMinMonoPayoff

double getMinMonoPayoff()

Calculates and returns the minimum payoff/score of individuals in monomorphic populations.

Returns:

the minimum payoff/score in monomorphic populations

getMaxMonoPayoff

double getMaxMonoPayoff()

Calculates and returns the maximum payoff/score of individuals in monomorphic populations.

Returns:

the maximum payoff/score in monomorphic populations

getMap2Fitness

Map2Fitness getMap2Fitness()

Gets the score/payoff to fitness map.

Returns:

the score-to-fitness map