Package org.evoludo.simulator.modules
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
Interface that all modules with frequency dependent fitness/payoffs should
implement. The classical
2x2
games is an example, see
TBT
.-
Nested Class Summary
Nested classes/interfaces inherited from interface Features
Features.Groups, Features.Multispecies, Features.Pairs, Features.Payoffs, Features.Static
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Method Summary
Modifier and TypeMethodDescriptionGets the score/payoff to fitness map.double
Calculates and returns the maximum payoff/score of individuals in monomorphic populations.double
Calculates and returns the maximum payoff/score of an individual.double
Calculates and returns the minimum payoff/score of individuals in monomorphic populations.double
Calculates and returns the minimum payoff/score of an individual.default boolean
Checks whether dynamic is neutral, i.e.Methods inherited from interface Features
getTitle, isMultispecies, isPairwise, isStatic
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Method Details
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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:
-
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:
-
isNeutral
default boolean isNeutral()Checks whether dynamic is neutral, i.e. no selection acting on the different traits.- Returns:
true
if all payoffs identical
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getMinMonoPayoff
double getMinMonoPayoff()Calculates and returns the minimum payoff/score of individuals in monomorphic populations.- Returns:
- the minimum payoff/score in monomorphic populations
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getMaxMonoPayoff
double getMaxMonoPayoff()Calculates and returns the maximum payoff/score of individuals in monomorphic populations.- Returns:
- the maximum payoff/score in monomorphic populations
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getMap2Fitness
Map2Fitness getMap2Fitness()Gets the score/payoff to fitness map.- Returns:
- the score-to-fitness map
-