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

public static interface IBS.HasIBS.MCPairs
extends IBS.HasIBS, Features.Pairs

Modules that offer individual based simulation models with multiple continuous traits and pairwise interactions must implement this interface.

Nested Class Summary

Nested classes/interfaces inherited from interface Features

Features.Groups, Features.Pairs, Features.Static

Nested 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 Type	Method	Description
double	pairScores(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

isStatic

Methods inherited from interface Features.Pairs

isPairwise

Methods inherited from interface IBS.HasIBS

createIBS

Method Details

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 traits me and the traits of its len interaction partners are given in group. 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 of len*nTraits entries. The payoffs/scores for each of the len opponent traits/strategies must be stored and returned in the array payoffs.

Note:

Only the first len entries in group are guaranteed to exist and have meaningful values. The population structure may restrict the size of the interaction group. len≤nGroup always holds.

Important:

must be overridden and implemented in subclasses that define game interactions between pairs of individuals (nGroup=2, pairwise=true), otherwise see IBS.HasIBS.CGroups.groupScores(double, double[], int, double[]).

Parameters:

me - the trait of the focal individual

groupTraits - the traits of the group members

len - the number of memebrs in the group

groupPayoffs - the array for returning the payoffs/scores for each group member

Returns:

the total (accumulated) payoff/score for the focal individual