// Async run helper function
public bool GeneratePrediction(PredictionGenerator predictor, BackgroundWorker worker)
{
predictor.RecursiveGetPredictions(Int32.Parse(predictIntervalsBox.Text));
string predictionDataPrintoutFile = DEFAULTDIRECTORY + "\\PredictionData_" + DateTime.Now.Month.ToString() + "-" +
DateTime.Now.Day.ToString() + "-" + DateTime.Now.Year.ToString() + "_" + DateTime.Now.Hour.ToString() +
DateTime.Now.Minute.ToString() + DateTime.Now.Second.ToString() + DateTime.Now.Millisecond.ToString() + ".csv";
predictor.WriteDataToCSV(predictionDataPrintoutFile);
return(true);
}
/// <summary>
/// Method to evolve set of traders.
/// </summary>
/// <param name="generations"> Number of generations to evolve over. </param>
/// <param name="genSize"> Number of traders in each generation. </param>
/// <param name="mutationRate"> Decimal random mutation rate. </param>
/// <returns> List of portfolio values over time for the most successful trader of the final generation. </returns>
public List <float> RunEvolution(int generations, int genSize, float mutationRate)
{
for (int i = 1; i < stockPrices.Count; i++)
{
Vector currentPctChgs = new Vector(stockPrices[i].Count());
for (int j = 0; j < stockPrices[i].Count(); j++)
{
currentPctChgs[j] = (stockPrices[i][j] - stockPrices[i - 1][j]) / stockPrices[i - 1][j];
}
predictor.GetNextPrediction(currentPctChgs);
predictor.RemoveOldestData();
}
predictor.WriteDataToCSV(MainForm.DEFAULTDIRECTORY + "\\PredictorData_" + DateTime.Now.Minute.ToString() + ".csv");
return(new List <float>());
}