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;
}
