//Misc
public static Population OverLearn(SimParams par, Population pop,
int[] vacant, List <int> notVacant)
{
//Get learners and tutors
List <int> Learners = vacant.ToList();
List <int>[] Tutors = ChooseMultipleTutors(par, pop, Learners, notVacant, par.NumTutorOverLearn);
List <int>[] TutorSyls = new List <int> [Learners.Count];
//Create combined song with all sylls
List <int>[] AllSongs;
List <int> CollapsedSongs;
for (int i = 0; i < Learners.Count; i++)
{
AllSongs = ListeningTest(par, pop, Tutors[i].ToArray(), par.ListeningThreshold);
CollapsedSongs = AllSongs.SelectMany(x => x).ToList();
TutorSyls[i] = CollapsedSongs.Distinct().ToList();
}
//Add Syls and update song traits
AddSyllables(par, pop, Learners, TutorSyls);
UpdateSongTraits(par, pop, Learners);
return(pop);
}
//Learning Accessory functions
private static ConsensusResults ConsensusLearning(SimParams par, Population pop,
List <int>[] tutors, List <int> learners)
{
//Create a consensus based on songs from several males
List <int>[] ConsensusSongs = new List <int> [learners.Count];
List <int>[] AddSyls = new List <int> [learners.Count];
List <int>[] AllSongs;
List <int> CollapsedSongs;
float Conform;
for (int i = 0; i < learners.Count; i++)
{
ConsensusSongs[i] = new List <int> {
};
AddSyls[i] = new List <int> {
};
AllSongs = ListeningTest(par, pop, tutors[i].ToArray(), par.ListeningThreshold);
CollapsedSongs = AllSongs.SelectMany(x => x).ToList();
ConsensusSongs[i] = CollapsedSongs.Distinct().ToList();
for (int j = 0; j < ConsensusSongs[i].Count(); j++)
{
Conform = ConsensusCalc(par, ConsensusSongs[i][j], CollapsedSongs);
if (par.NextFloat() < Conform)
{
AddSyls[i].Add(ConsensusSongs[i][j]);
}
}
}
ConsensusResults Returnable = new ConsensusResults(AddSyls, ConsensusSongs);
return(Returnable);
}
