Add progression and new method of selection/mutation/crossover

src/Managing.Application/GeneticService.cs

@@ -21,6 +21,7 @@ public class GeneticService : IGeneticService
     private readonly IGeneticRepository _geneticRepository;
     private readonly IBacktester _backtester;
     private readonly ILogger<GeneticService> _logger;
+    private readonly IMessengerService _messengerService;
 
     // Predefined parameter ranges for each indicator (matching backtestGenetic.tsx)
     public static readonly Dictionary<string, (double min, double max)> ParameterRanges = new()
@@ -186,11 +187,13 @@ public class GeneticService : IGeneticService
     public GeneticService(
         IGeneticRepository geneticRepository,
         IBacktester backtester,
-        ILogger<GeneticService> logger)
+        ILogger<GeneticService> logger,
+        IMessengerService messengerService)
     {
         _geneticRepository = geneticRepository;
         _backtester = backtester;
         _logger = logger;
+        _messengerService = messengerService;
     }
 
     public GeneticRequest CreateGeneticRequest(
@@ -204,6 +207,8 @@ public class GeneticService : IGeneticService
         int generations,
         double mutationRate,
         GeneticSelectionMethod selectionMethod,
+        GeneticCrossoverMethod crossoverMethod,
+        GeneticMutationMethod mutationMethod,
         int elitismPercentage,
         double maxTakeProfit,
         List<IndicatorType> eligibleIndicators)
@@ -220,6 +225,8 @@ public class GeneticService : IGeneticService
             Generations = generations,
             MutationRate = mutationRate,
             SelectionMethod = selectionMethod,
+            CrossoverMethod = crossoverMethod,
+            MutationMethod = mutationMethod,
             ElitismPercentage = elitismPercentage,
             MaxTakeProfit = maxTakeProfit,
             EligibleIndicators = eligibleIndicators,
@@ -307,8 +314,8 @@ public class GeneticService : IGeneticService
                 population,
                 fitness,
                 GetSelection(request.SelectionMethod),
-                new UniformCrossover(),
-                GetMutation(request.MutationRate))
+                GetCrossover(request.CrossoverMethod),
+                GetMutation(request.MutationMethod))
             {
                 Termination = new GenerationNumberTermination(request.Generations),
                 MutationProbability = (float)request.MutationRate,
@@ -330,28 +337,25 @@ public class GeneticService : IGeneticService
             {
                 generationCount = ga.GenerationsNumber;
 
-                // Update progress every 5 generations
-                if (generationCount % 5 == 0)
+                // Update progress every generation
+                var bestFitness = ga.BestChromosome?.Fitness ?? 0;
+                request.CurrentGeneration = generationCount;
+                request.BestFitnessSoFar = bestFitness;
+
+                if (ga.BestChromosome is TradingBotChromosome bestChromosome)
                 {
-                    var bestFitness = ga.BestChromosome?.Fitness ?? 0;
-                    request.CurrentGeneration = generationCount;
-                    request.BestFitnessSoFar = bestFitness;
-
-                    if (ga.BestChromosome is TradingBotChromosome bestChromosome)
+                    var genes = bestChromosome.GetGenes();
+                    var geneValues = genes.Select(g =>
                     {
-                        var genes = bestChromosome.GetGenes();
-                        var geneValues = genes.Select(g =>
-                        {
-                            if (g.Value is double doubleValue) return doubleValue;
-                            if (g.Value is int intValue) return (double)intValue;
-                            return Convert.ToDouble(g.Value.ToString());
-                        }).ToArray();
-                        request.BestChromosome = JsonSerializer.Serialize(geneValues);
-                    }
-
-                    UpdateGeneticRequest(request);
+                        if (g.Value is double doubleValue) return doubleValue;
+                        if (g.Value is int intValue) return (double)intValue;
+                        return Convert.ToDouble(g.Value.ToString());
+                    }).ToArray();
+                    request.BestChromosome = JsonSerializer.Serialize(geneValues);
                 }
 
+                UpdateGeneticRequest(request);
+
                 // Check for cancellation
                 if (cancellationToken.IsCancellationRequested)
                 {
@@ -403,6 +407,16 @@ public class GeneticService : IGeneticService
 
             UpdateGeneticRequest(request);
 
+            // Send notification about the completed genetic algorithm
+            try
+            {
+                await _messengerService.SendGeneticAlgorithmNotification(request, bestFitness, bestChromosome);
+            }
+            catch (Exception notificationEx)
+            {
+                _logger.LogWarning(notificationEx, "Failed to send genetic algorithm notification for request {RequestId}", request.RequestId);
+            }
+
             return new GeneticAlgorithmResult
             {
                 BestFitness = bestFitness,
@@ -429,16 +443,48 @@ public class GeneticService : IGeneticService
     {
         return selectionMethod switch
         {
-            GeneticSelectionMethod.Tournament => new TournamentSelection(),
+            GeneticSelectionMethod.Elite => new EliteSelection(),
             GeneticSelectionMethod.Roulette => new RouletteWheelSelection(),
-            GeneticSelectionMethod.FitnessWeighted => new RankSelection(), // Use rank selection as approximation
+            GeneticSelectionMethod.StochasticUniversalSampling => new StochasticUniversalSamplingSelection(),
+            GeneticSelectionMethod.Tournament => new TournamentSelection(),
+            GeneticSelectionMethod.Truncation => new TruncationSelection(),
             _ => new TournamentSelection()
         };
     }
 
-    private IMutation GetMutation(double mutationRate)
+    private ICrossover GetCrossover(GeneticCrossoverMethod crossoverMethod)
     {
-        return new UniformMutation(true);
+        return crossoverMethod switch
+        {
+            GeneticCrossoverMethod.AlternatingPosition => new AlternatingPositionCrossover(),
+            GeneticCrossoverMethod.CutAndSplice => new CutAndSpliceCrossover(),
+            GeneticCrossoverMethod.Cycle => new CycleCrossover(),
+            GeneticCrossoverMethod.OnePoint => new OnePointCrossover(),
+            GeneticCrossoverMethod.OrderBased => new OrderBasedCrossover(),
+            GeneticCrossoverMethod.Ordered => new OrderedCrossover(),
+            GeneticCrossoverMethod.PartiallyMapped => new PartiallyMappedCrossover(),
+            GeneticCrossoverMethod.PositionBased => new PositionBasedCrossover(),
+            GeneticCrossoverMethod.ThreeParent => new ThreeParentCrossover(),
+            GeneticCrossoverMethod.TwoPoint => new TwoPointCrossover(),
+            GeneticCrossoverMethod.Uniform => new UniformCrossover(),
+            GeneticCrossoverMethod.VotingRecombination => new VotingRecombinationCrossover(),
+            _ => new UniformCrossover()
+        };
+    }
+
+    private IMutation GetMutation(GeneticMutationMethod mutationMethod)
+    {
+        return mutationMethod switch
+        {
+            GeneticMutationMethod.Displacement => new DisplacementMutation(),
+            GeneticMutationMethod.FlipBit => new FlipBitMutation(),
+            GeneticMutationMethod.Insertion => new InsertionMutation(),
+            GeneticMutationMethod.PartialShuffle => new PartialShuffleMutation(),
+            GeneticMutationMethod.ReverseSequence => new ReverseSequenceMutation(),
+            GeneticMutationMethod.Twors => new TworsMutation(),
+            GeneticMutationMethod.Uniform => new UniformMutation(true),
+            _ => new UniformMutation(true)
+        };
     }
 }
 

src/Managing.Application/Shared/MessengerService.cs

@@ -176,6 +176,19 @@ public class MessengerService : IMessengerService
         }
     }
 
+    public async Task SendGeneticAlgorithmNotification(GeneticRequest request, double bestFitness, object? bestChromosome)
+    {
+        try
+        {
+            var message = BuildGeneticAlgorithmMessage(request, bestFitness, bestChromosome);
+            await _webhookService.SendMessage(message, "2775292276");
+        }
+        catch (Exception e)
+        {
+            Console.WriteLine($"Failed to send genetic algorithm notification: {e.Message}");
+        }
+    }
+
     private string BuildBacktestConfigMessage(Backtest backtest)
     {
         var config = backtest.Config;
@@ -263,4 +276,42 @@ public class MessengerService : IMessengerService
 
         return message;
     }
+
+    private string BuildGeneticAlgorithmMessage(GeneticRequest request, double bestFitness, object? bestChromosome)
+    {
+        var duration = request.CompletedAt.HasValue 
+            ? request.CompletedAt.Value - request.CreatedAt 
+            : TimeSpan.Zero;
+
+        var indicators = request.EligibleIndicators.Any() 
+            ? string.Join(", ", request.EligibleIndicators.Select(i => i.ToString()))
+            : "N/A";
+
+        if (request.EligibleIndicators.Count > 5)
+        {
+            indicators += $" (+{request.EligibleIndicators.Count - 5} more)";
+        }
+
+        var message = $"🧬 Genetic Algorithm Completed! 🧬\n\n" +
+                      $"🔹 Symbol: {request.Ticker}\n" +
+                      $"⏱️ Timeframe: {request.Timeframe}\n" +
+                      $"👥 Population: {request.PopulationSize}\n" +
+                      $"🔄 Generations: {request.Generations}\n" +
+                      $"🎯 Selection: {request.SelectionMethod}\n" +
+                      $"🔀 Crossover: {request.CrossoverMethod}\n" +
+                      $"🧬 Mutation: {request.MutationMethod}\n" +
+                      $"🧩 Indicators: {indicators}\n" +
+                      $"📅 Period: {request.StartDate:yyyy-MM-dd} to {request.EndDate:yyyy-MM-dd}\n" +
+                      $"📈 Results:\n" +
+                      $"⭐ Best Fitness: {bestFitness:F4}\n" +
+                      $"⏱️ Duration: {duration.TotalMinutes:F1} minutes\n" +
+                      $"🆔 Request ID: {request.RequestId[..8]}...";
+
+        if (request.BestFitnessSoFar.HasValue && request.BestFitnessSoFar.Value > 0)
+        {
+            message += $"\n🏆 Best Fitness So Far: {request.BestFitnessSoFar.Value:F4}";
+        }
+
+        return message;
+    }
 }