/// <summary>
/// Add the genres and their associated albums either to the next or a new population
/// </summary>
/// <param name="populationIndex"></param>
/// <param name="genres"></param>
public void AddToPopulation(int populationIndex, IEnumerable <string> genres)
{
// Make sure that there are some genres and albums that have not been seen before
// Use a List here as having the GenresAlreadyIncluded modifier in the .where seems to cause problems with Linq lazy evaluation
List <string> newGenres = genres.Where(gen => GenresAlreadyIncluded.Add(gen) == true).ToList();
if (newGenres.Count > 0)
{
// Are there any albums associated with these genres that have not been seen before
List <Album> newAlbums = GetAlbumsFromGenres(newGenres);
if (newAlbums.Count > 0)
{
// Add these entries to the next population to the one just used. If the one just used was the last one then create a new population
if (populationIndex == (Populations.Count - 1))
{
// A new population is required
Populations.Add(new Population(GenrePopulations.CreatePopulation(Id, Populations.Count, newGenres), newGenres, newAlbums));
}
else
{
// Add the genres and albums to the existing Population
Populations[populationIndex + 1].Add(newGenres, newAlbums);
}
}
}
}
/// <summary>
/// Form the initial population from all the genres and albums that can be reached from the specified initial set of genres
/// </summary>
/// <param name="startingGenres"></param>
public void AddAllReachableGenres(IEnumerable <string> startingGenres)
{
List <string> newGenres = null;
List <Album> newAlbums = null;
int expansionCount = 0;
// Start with the initial genres
List <string> currentGenres = startingGenres.ToList();
do
{
// Are there any genres that have not been seen before
newGenres = currentGenres.Where(gen => GenresAlreadyIncluded.Add(gen) == true).ToList();
if (newGenres.Count > 0)
{
// Are there any albums associated with these genres that have not been seen before
newAlbums = GetAlbumsFromGenres(newGenres);
if (newAlbums.Count > 0)
{
// Get all the genres associated with these new albums
currentGenres = newAlbums.SelectMany(alb => alb.Genre.Split(';')).ToList();
}
}
}while ((newGenres.Count > 0) && (newAlbums.Count > 0) && ((FastSpreadLimit == 0) || (++expansionCount < FastSpreadLimit)));
// Unload the genres and albums from the HashSets and use to generate the first population
Populations.Add(new Population(GenrePopulations.CreatePopulation(Id, Populations.Count, GenresAlreadyIncluded.ToList()),
GenresAlreadyIncluded.ToList(), Albums.AlbumCollection.Where(alb => AlbumsAlreadyIncluded.Contains(alb.Id))));
}
public Chromosomes.IChromosome[] PerformSelection(Populations.IPopulation population, int size)
{
//Getting all of the chromosomes that are in population.
Chromosomes.IChromosome[] individuals = population.GetChromosomes ();
//Calculating the number of the those chromosomes.
int sz = individuals.Length;
//Calculating the fitness of each chromosome.
double[] f = new double[sz];
double[] fitnesses = population.GetFitnesses();
for (int i = 0; i < sz; ++i)
f[i] = fitnesses[i];
//Sorting the population by descending fitness values.
Sort (individuals, f, 0, sz - 1);
//Defining the to-be-returned array.
Chromosomes.IChromosome[] ret = new Chromosomes.IChromosome[size];
//Selecting the parents from the population and putting them in ret.
for (int i = 0; i < size; ++i)
ret[i] = individuals[i].Clone();
//Returning the result.
return ret;
}
public Chromosomes.IChromosome[] PerformSelection(Populations.IPopulation population, int size)
{
//Getting all of the chromosomes that are in population.
Chromosomes.IChromosome[] individuals = population.GetChromosomes();
//Calculating the number of the those chromosomes.
int sz = individuals.Length;
//Calculating the fitness of each chromosome.
double[] f = new double[sz];
double[] fitnesses = population.GetFitnesses();
for (int i = 0; i < sz; ++i)
f[i] = fitnesses[i];
//Defining the to-be-returned array.
Chromosomes.IChromosome[] ret = new Chromosomes.IChromosome[size];
//Selecting the parents from the population and putting them in ret.
for (int i = 0; i < size; ++i)
{
int parentidx=-1;
for (int j=0;j<TournamentSize;++j){
int idx=random.Next(size);
if (parentidx==-1||f[parentidx]<f[idx]){
parentidx=idx;
}
}
ret[i]=individuals[parentidx].Clone();
}
//Returning the result.
return ret;
}
public override string ToString()
{
//JAVA TO C# CONVERTER TODO TASK: Most Java stream collectors are not converted by Java to C# Converter:
string updatesString = Populations.Select(population => population.batchedUpdates.size() + " updates").collect(joining(", ", "[", "]"));
return("BatchingMultipleIndexPopulator{activeTasks=" + _activeTasks + ", executor=" + _executor + ", " +
"batchedUpdates = " + updatesString + ", queuedUpdates = " + UpdatesQueue.Count + "}");
}
protected void UpdateMaxNodes(IMap map)
{
var atualNodes = Populations.Sum(o => o.ListNodes.Count);
if (atualNodes >= map.GetMaxExpandedNodes())
{
map.SetMaxExpandedNodes(atualNodes);
}
}
private async Task CalcFitness()
{
await CalcGenomeRoutesAsync();
Populations.ForEach(e => e.CalcFitness(Fitness));
Populations = Populations
.OrderBy(o => o.Fitness).ToList();
/*.OrderBy(e =>
* e.Trucks.Any(t => t.Routes.Any(r => r.Late)))
* .ThenBy(o => o.Fitness).ToList();*/
}
/// <summary>
/// Remove a population from the RPM.
/// </summary>
public void RemovePopulation(Population population)
{
if (!Populations.Contains(population))
{
return;
}
Populations.Remove(population);
TypesOfTerrain.Remove(population);
openID.Enqueue(PopulationToID[population]);
PopulationByID.Remove(PopulationToID[population]); // free ID
PopulationToID.Remove(population); // free ID
CleanupAccessMapForRecycledID();
}
internal override void Plus(XDocument xdoc)
{
foreach (var element in xdoc.Root.Elements())
{
var val = element.Value;
int valI;
int.TryParse(val, out valI);
switch (element.Name.LocalName)
{
case "id":
case "type":
break;
case "coords":
if (Coords == null)
{
Coords = new List <Point>();
}
foreach (var coordSplit in val.Split(new[] { '|' }, StringSplitOptions.RemoveEmptyEntries).Select(coord => coord.Split(',')).Where(coordSplit => coordSplit.Length == 2))
{
Coords.Add(new Point(Convert.ToInt32(coordSplit[0]), Convert.ToInt32(coordSplit[1])));
}
break;
case "population":
if (Populations == null)
{
Populations = new Dictionary <Race, int>();
}
foreach (var popSplit in val.Split(new[] { '|' }, StringSplitOptions.RemoveEmptyEntries).Select(pop => pop.Split(',')).Where(popSplit => popSplit.Length == 3))
{
if (Populations.ContainsKey(World.Races[Convert.ToInt32(popSplit[0])]))
{
Populations[World.Races[Convert.ToInt32(popSplit[0])]] += Convert.ToInt32(popSplit[1]);
}
else
{
Populations.Add(World.Races[Convert.ToInt32(popSplit[0])], Convert.ToInt32(popSplit[1]));
}
}
break;
default:
DFXMLParser.UnexpectedXmlElement(xdoc.Root.Name.LocalName + "\t" + "Region", element, xdoc.Root.ToString());
break;
}
}
}
public EconomicsViewModel()
{
Factions = GameState.Instance.Factions;
if (Factions == null)
{
return;
}
CurrentFaction = Factions.FirstOrDefault();
if (Populations != null)
{
CurrentPopulation = Populations.FirstOrDefault();
}
}
public Builder setPopulation(PopulationType populationType, int count)
{
if (count == 0)
{
Populations.Remove(populationType);
return(this);
}
if (Populations.ContainsKey(populationType))
{
Populations[populationType] = count;
}
else
{
Populations.Add(populationType, count);
}
return(this);
}
async Task CalcGenomeRoutesAsync()
{
if (ProcessChunk == 1)
{
foreach (var item in Populations)
{
await item.CalcRoutesAsync(routeService);
}
}
else
{
await Populations
.ToObservable(ThreadPoolScheduler.Instance)
.Select(n => Observable.FromAsync(_ => n.CalcRoutesAsync(routeService)))
.Merge(ProcessChunk);
}
}
public void AddPopulations(List <Population> populations)
{
foreach (Population population in populations)
{
Population popMatch = Populations.FirstOrDefault(pop => pop.Race.NamePlural.Equals(population.Race.NamePlural, StringComparison.InvariantCultureIgnoreCase));
if (popMatch != null)
{
popMatch.Count += population.Count;
}
else
{
Populations.Add(new Population(population.Race, population.Count));
}
}
Populations = Populations.OrderByDescending(pop => pop.Count).ToList();
Parent?.AddPopulations(populations);
}
public void AddPopulations(List <Population> populations)
{
foreach (Population population in populations)
{
Population popMatch = Populations.FirstOrDefault(pop => pop.Race == population.Race);
if (popMatch != null)
{
popMatch.Count += population.Count;
}
else
{
Populations.Add(new Population(population.Race, population.Count));
}
}
Populations = Populations.OrderByDescending(pop => pop.Count).ToList();
Parent?.AddPopulations(populations);
}
/// <summary>
/// Clear the Population and SeedGenres entries
/// </summary>
public void Clear()
{
foreach (Population population in Populations)
{
GenrePopulations.RemovePopulation(population.SeedPopulation);
}
if (SeedGenres != null)
{
GenrePopulations.RemovePopulation(SeedGenres);
SeedGenres = null;
}
Populations.Clear();
GenresAlreadyIncluded.Clear();
AlbumsAlreadyIncluded.Clear();
}
private void removeRow(object obj)
{
Population tempPop = new Population();
tempPop.Date = SelectedPopulation.Date;
tempPop.Sex = SelectedPopulation.Sex;
tempPop.Value = SelectedPopulation.Value;
for (int i = 0; i < Populations.Count(); i++)
{
if ((Populations[i].Date.Equals(tempPop.Date)) && (Populations[i].Sex.Equals(tempPop.Sex)) &&
(Populations[i].Value.Equals(tempPop.Value)))
{
Populations.RemoveAt(i);
}
}
}
public void UpdatePopulations()
{
if (SelectedSort == 0)//enum
{
populations = populations.OrderBy(p => p.City).ToList();
}
else
{
populations = populations.OrderByDescending(p => p.PopulationNum).ToList();
}
Populations.Clear();
foreach (Population p in populations)
{
Populations.Add(p);
}
}
private static List <Populations> GetPopulations()
{
var pops = new List <Populations>();
var populations = File.ReadAllLines(filePath + "Populations.txt");
foreach (var item in populations)
{
var info = item.Split(' ');
var newPop = new Populations
{
Iso3 = info[0],
Population = double.Parse(info[1])
};
pops.Add(newPop);
}
return(pops);
}
/// <summary>
/// Add a population to the RPM.
/// </summary>
public void AddPopulation(Population population)
{
if (!Populations.Contains(population))
{
// ignore their old id and assign it a new one
int id = openID.Dequeue();
// since IDs after maxPopulation-1 are recycled ids, we need to do clean up old values
if (id == lastRecycledID)
{
CleanupAccessMapForRecycledID();
}
PopulationToID.Add(population, id);
PopulationByID.Add(id, population);
Populations.Add(population);
TypesOfTerrain.Add(population, new int[(int)TileType.TypesOfTiles]);
// generate the map with the new id
GenerateMap(population);
}
}
/// <summary>
/// Intialise the Population list from the GenrePopulation records
/// </summary>
public void InitialisePopulations()
{
// Get all the GenrePopulation records associated with this Autoplay and order by the population index
IEnumerable <GenrePopulation> genrePopulations = GenrePopulations.GenrePopulationCollection.Where(gp => gp.AutoplayId == Id).OrderBy(gp => gp.Index);
// Create a Population for each GenrePopulation and add it to the list
foreach (GenrePopulation population in genrePopulations)
{
// If this is the original set of genres then save it separately
if (population.Index == -1)
{
SeedGenres = population;
}
else
{
// Get all the new genres and albums
List <string> populationGenres = population.Genres.Where(gen => GenresAlreadyIncluded.Add(gen) == true).ToList();
IEnumerable <Album> populationAlbums = GetAlbumsFromGenres(populationGenres);
Populations.Add(new Population(population, populationGenres, populationAlbums));
}
}
}
public async Task <Genome> FindPathAsync(Roteiro map, Genome seed = null)
{
if (Mutate == null || Crossover == null || Fitness == null || Selection == null)
{
throw new System.Exception("GA cant run without all operators");
}
var locals = map.Destinations.ToList();
locals.Add(map.Depot);
await routeService.Prepare(locals);
var rand = RandomSingleton.Instance;
var startNode = map.Depot;
Populations.Clear();
var popusize = PopulationSize;
if (seed != null)
{
Populations.Add(seed);
popusize--;
}
Populations.AddRange(
Enumerable.Range(0, popusize)
.Select(_ => Genome.Generator(map, Settings)));
await CalcFitness();
for (int i = 0; i < GenerationLimit; i++)
{
var newpopulations = new List <Genome>();
for (int j = 0; j < BestSolutionToPick; j++)
{
newpopulations.Add(Populations[j]);
}
while (newpopulations.Count < Populations.Count)
{
if (newpopulations.Any(e => e.Trucks.SelectMany(l => l.Locals).Count() != map.Destinations.Count))
{
throw new System.Exception();
}
// Selection
var(nodemom, nodedad) = Selection.SelectCouple(Populations);
// CrossOver
var sons = Crossover.Make(nodemom, nodedad);
// Mutation
sons = sons.Select(s => Mutate.Apply(s)).ToArray();
newpopulations.AddRange(sons);
}
Populations = newpopulations.ToList();
await CalcFitness();
Best = Populations.First();
}
return(Best);
}
public override bool Find(IMap map, IHeuristic heuristic)
{
if (Mutate == null || Crossover == null || Fitness == null || Selection == null)
{
throw new System.Exception("GA cant run without all operators");
}
if (Fitness.Heuristic == null)
{
Fitness.Heuristic = heuristic;
}
var Adaptation = new Adaptation(map);
var rand = RandomFactory.Rand;
var startNode = map.StartNode;
var endNode = map.EndNode;
for (int i = 0; i < PopulationSize; i++)
{
Populations.Add(new Genome(map));
}
CalcFitness();
var step = 0;
OnStart(BuildArgs(step, map));
for (int i = 0; i < GenerationLimit; i++)
{
var newpopulations = new List <IGenome>();
Populations = Populations.OrderBy(o => o.Fitness).ToList();
for (int j = 0; j < BestSolutionToPick; j++)
{
Populations[j].Fitness = Fitness.Calc(Populations[j]);
newpopulations.Add(Populations[j]);
}
var ran = rand.Next(1, Populations.Count);
var best = Populations.First().ListNodes;
var best2 = Selection.Select(Populations).ListNodes;
endNode = best.Last();
if (endNode.Equals(map.EndNode))
{
endNode.Direction = DirectionMovement.None;
map.EndNode = endNode;
map.UpdateClosedList(new List <Node>());
map.UpdateOpenList(new List <Node>());
//if (!best.First().Equals(map.StartNode))
OnEnd(BuildArgs(step, map, true));
Generations = i;
return(true);
}
map.UpdateClosedList(best);
map.UpdateOpenList(best2);
while (newpopulations.Count < Populations.Count)
{
// Selection
var nodemom = Selection.Select(Populations);
var nodedad = Selection.Select(Populations);
// CrossOver
var cross = Crossover.Calc(new CrossoverOperation(nodemom, nodedad));
//if (!cross.Mom.ListNodes.First().Equals(map.StartNode)) { }
//if (!cross.Dad.ListNodes.First().Equals(map.StartNode)) { }
// Mutation
nodemom = Mutate.Calc(cross.Mom);
nodedad = Mutate.Calc(cross.Dad);
//if (!nodemom.ListNodes.First().Equals(map.StartNode)) { }
//if (!nodedad.ListNodes.First().Equals(map.StartNode)) { }
// Adaptation
nodemom = Adaptation.Calc(nodemom);
nodedad = Adaptation.Calc(nodedad);
nodemom.Fitness = Fitness.Calc(nodemom);
nodedad.Fitness = Fitness.Calc(nodedad);
//if (!nodemom.ListNodes.First().Equals(map.StartNode)) { }
//if (!nodedad.ListNodes.First().Equals(map.StartNode)) { }
// Add in new population
newpopulations.Add(nodemom);
newpopulations.Add(nodedad);
}
Populations = newpopulations.ToList();
OnStep(BuildArgs(step++, map));
}
Generations = GenerationLimit;
OnEnd(BuildArgs(step, map, false));
return(false);
}
public Chromosomes.IChromosome[] PerformSelection(Populations.IPopulation population, int size)
{
//Getting all of the chromosomes that are in population.
Chromosomes.IChromosome[] individuals = population.GetChromosomes();
//Calculating the number of the those chromosomes.
int sz = individuals.Length;
//Calculating the fitness of each chromosome.
double[] f = new double[sz];
double[] fitnesses = population.GetFitnesses();
for (int i = 0; i < sz; ++i)
f[i] = fitnesses[i];
//Calculating the sum of the fitnesses.
double sum = 0.0;
for (int i = 0; i < sz; ++i)
sum += f[i];
//The normalization step.
for (int i = 0; i < sz; ++i)
f[i] /= sum;
//Sorting the population by descending fitness values.
RouletteWheelSelectionMethod.Sort(individuals, f, 0, sz - 1);
//The accumulation step.
for (int i = 1; i < sz; ++i)
f[i] += f[i - 1];
f[sz - 1] = 1.0; //To ensure that the sum of all the fitnesses is equal to 1.0.
//Defining the to-be-returned array.
Chromosomes.IChromosome[] ret = new Chromosomes.IChromosome[size];
//Selecting the parents from the population and putting them in ret.
for (int i = 0; i < size; ++i)
{
int idx = RouletteWheelSelectionMethod.Find(f, RouletteWheelSelectionMethod.random.NextDouble());
ret[i] = individuals[idx].Clone();
}
//Returning the result.
return ret;
}
public void Dirty()
{
Populations.Dirty();
ResearchTable.Dirty();
}
