public PersonScenarioExperimental( IClientFactory clientFactory, ITrainerFactory trainerFactory, IGetTrainerForClient getTrainerForClient, IDatabase database, [KeyFilter("FacadeLogger")] ILogger logger) { this.clientFactory = clientFactory; this.trainerFactory = trainerFactory; this.getTrainerForClient = getTrainerForClient; this.database = database; this.logger = logger; }
public InteractionManager(ILogger logger) { this.trainers = new HashSet<ITrainer>(); this.students = new HashSet<IStudent>(); this.studentFactory = new StudentFactory(); this.trainerFactory = new TrainerFactory(); this.petFactory = new PetFactory(); this.logger = logger; GeneratePreviousYearTrainers(); }
public InteractionManager(ILogger logger) { this.trainers = new HashSet <ITrainer>(); this.students = new HashSet <IStudent>(); this.studentFactory = new StudentFactory(); this.trainerFactory = new TrainerFactory(); this.petFactory = new PetFactory(); this.logger = logger; GeneratePreviousYearTrainers(); }
private void GaGeneratePredictionsButton_Click(object sender, EventArgs e) { LockAllTabPages(); _windowWidth = _gaWindowWidth; _operationStart = DateTime.Now; _outputFilename = Utilities.OutputFileName("geneGUI.csv"); _lengthOfPrediction = _gaLengthOfPrediction; _startDayIndex = _gaStartDay; _trainerFactory = new GeneticTrainerFactory((float)_gaMutationRate, (float)_gaCrossoverRate, _gaIterations); _backgroundWorker = new BackgroundWorker(); _backgroundWorker.WorkerReportsProgress = true; _backgroundWorker.WorkerSupportsCancellation = true; _backgroundWorker.DoWork += BackgroundWorkerDoWork; _backgroundWorker.RunWorkerCompleted += _backgroundWorker_RunWorkerCompleted; var progressForm = new ProgressForm(_backgroundWorker); progressForm.Show(); }
private void AcorGeneratePredictionsButton_Click(object sender, EventArgs e) { //LockAllTabPagesButMe(); LockAllTabPages(); _windowWidth = _acorWindowWidth; _operationStart = DateTime.Now; _outputFilename = Utilities.OutputFileName("antsGUI.csv"); _lengthOfPrediction = _acorLengthOfPrediction; _startDayIndex = _acorStartDay; _trainerFactory = new ACORTrainerFactory(_acorQ, _acorEpsilon, _acorIterations); _backgroundWorker = new BackgroundWorker(); _backgroundWorker.WorkerReportsProgress = true; _backgroundWorker.WorkerSupportsCancellation = true; _backgroundWorker.DoWork += BackgroundWorkerDoWork; _backgroundWorker.RunWorkerCompleted += _backgroundWorker_RunWorkerCompleted; var progressForm = new ProgressForm(_backgroundWorker); progressForm.Show(); }
static void Main(string[] args) { //CultureInfo culture = new CultureInfo("en"); //CultureInfo.DefaultThreadCurrentCulture = culture; if (args.Length < 1) { //PrintHelp(); _mainKasandraForm = new MainKasandraForm(); Application.EnableVisualStyles(); //Application.SetCompatibleTextRenderingDefault(false); Application.Run(_mainKasandraForm); } else if(args.Length == 1) { PrintHelp(); } else { _inputFilename = args[1].Trim(); string command = "days"; if (args.Contains(command)) { int daysIndex = 0; for (int i = 0; i < args.Length; i++) if (args[i] == command) { daysIndex = i; break; } try { _startDayIndex = Int32.Parse(args[daysIndex + 1]); _howManyDaysToPredict = Int32.Parse(args[daysIndex+2]); _teachHowManyDays = Int32.Parse(args[daysIndex + 3]); } catch { } } switch (args[0]) { case "a": { _predictionOutputFilename = Utilities.OutputFileName("ants.csv"); double q = 0; double epsilon = 0; int archSize = 0; int iterations = 0; bool ok = true; try { q = Double.Parse(args[2]); epsilon = Double.Parse(args[3]); archSize = Int32.Parse(args[4]); iterations = Int32.Parse(args[5]); } catch (Exception) { ok = false; } _trainerFactory = ok ? new ACORTrainerFactory(q, epsilon, iterations, archSize) : new ACORTrainerFactory(); if (_parallel) { GeneratePredictionsParallel(_inputFilename, _teachHowManyDays); } else { GeneratePredictionsSequential(_inputFilename, _teachHowManyDays); } break; } case "g": { _predictionOutputFilename = Utilities.OutputFileName("gene.csv"); float m = 0; float c = 0; int pmax = 0; int pmin = 0; int iterations = 0; bool ok = true; try { m = (float)Double.Parse(args[2]); c = (float)Double.Parse(args[3]); pmax = Int32.Parse(args[4]); pmin = Int32.Parse(args[5]); iterations = Int32.Parse(args[6]); } catch (Exception) { ok = false; } _trainerFactory = ok ? new GeneticTrainerFactory(m, c, iterations, pmax, pmin) : new GeneticTrainerFactory(); if(_parallel) { GeneratePredictionsParallel(_inputFilename, _teachHowManyDays);} else { GeneratePredictionsSequential(_inputFilename, _teachHowManyDays);} break; } case "n": { NormalizeInputFile(_inputFilename); break; } case "i": { string _predictionsFile; try { _predictionsFile = args[2].Trim(); if (!File.Exists(_predictionsFile)) { Console.WriteLine("Please provide existing file with precalculated predictions"); break; } } catch (Exception) { PrintHelp(); break; } InvestmentSimulations(_inputFilename, _predictionsFile); break; } case "r": { GenerateRandomPredictions(); break; } default: { PrintHelp(); break; } } } //return; }