Package org.evoludo.simulator.models
Interface IBS.HasIBS.MCPairs
- All Superinterfaces:
Features,Features.Pairs,IBS.HasIBS
- All Known Implementing Classes:
CLabour
- Enclosing interface:
IBS.HasIBS
Modules that offer individual based simulation models with multiple
continuous traits and pairwise interactions must implement this interface.
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Nested Class Summary
Nested classes/interfaces inherited from interface Features
Features.Groups, Features.Multispecies, Features.Pairs, Features.Payoffs, Features.StaticNested classes/interfaces inherited from interface IBS.HasIBS
IBS.HasIBS.CGroups, IBS.HasIBS.CPairs, IBS.HasIBS.DGroups, IBS.HasIBS.DPairs, IBS.HasIBS.MCGroups, IBS.HasIBS.MCPairs -
Method Summary
Modifier and TypeMethodDescriptiondoublepairScores(double[] me, double[] groupTraits, int len, double[] groupPayoffs) Calculate the payoff/score for modules with interactions in pairs and multiple continuous traits.Methods inherited from interface Features
getTitle, isMultispecies, isStaticMethods inherited from interface Features.Pairs
isPairwiseMethods inherited from interface IBS.HasIBS
createIBS
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Method Details
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pairScores
double pairScores(double[] me, double[] groupTraits, int len, double[] groupPayoffs) Calculate the payoff/score for modules with interactions in pairs and multiple continuous traits. The focal individual has traitsmeand the traits of itsleninteraction partners are given ingroup. The traits they are arranged in the usual manner, i.e. first all traits of the first group member then all traits by the second group member etc. for a total oflen*nTraitsentries. The payoffs/scores for each of thelenopponent traits must be stored and returned in the arraypayoffs.Note:
Only the firstlenentries ingroupare guaranteed to exist and have meaningful values. The population structure may restrict the size of the interaction group.len≤nGroupalways holds.Important:
must be overridden and implemented in subclasses that define game interactions between pairs of individuals (nGroup=2,pairwise=true), otherwise seeIBS.HasIBS.CGroups.groupScores(double, double[], int, double[]).- Parameters:
me- the trait of the focal individualgroupTraits- the traits of the group memberslen- the number of memebrs in the groupgroupPayoffs- the array for returning the payoffs/scores for each group member- Returns:
- the total (accumulated) payoff/score for the focal individual
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