/// <summary>
/// Represents the strategy in a readable form.
/// </summary>
public override string ToString()
{
string str = String.Empty;
string nl = Environment.NewLine;
string nl2 = Environment.NewLine + Environment.NewLine;
str += "Strategy Name - " + strategyName + nl;
str += "Symbol - " + Symbol + nl;
str += "Period - " + DataPeriod.ToString() + nl;
str += "Same dir signal - " + sameDirSignlAct.ToString() + nl;
str += "Opposite dir signal - " + oppDirSignlAct.ToString() + nl;
str += "Use account % entry - " + UseAccountPercentEntry + nl;
str += "Max open lots - " + MaxOpenLots + nl;
str += "Entry lots - " + EntryLots + nl;
str += "Adding lots - " + AddingLots + nl;
str += "Reducing lots - " + ReducingLots + nl;
str += "Use Permanent S/L - " + usePermanentSL.ToString() + nl;
str += "Permanent S/L - " + permanentSLType.ToString() + " " + permanentSL.ToString() + nl;
str += "Use Permanent T/P - " + usePermanentTP.ToString() + nl;
str += "Permanent T/P - " + permanentTPType.ToString() + " " + permanentTP.ToString() + nl;
str += "Use Break Even - " + useBreakEven.ToString() + nl;
str += "Break Even - " + breakEven.ToString() + " " + permanentTP.ToString() + nl2;
str += "Description" + nl2 + nl;
for (int iSlot = 0; iSlot < Slots; iSlot++)
{
str += Slot[iSlot].SlotType.ToString() + nl;
str += indicatorSlot[iSlot].IndParam.ToString() + nl2;
}
return(str);
}
//public List<sp_Forecast_GetDailyAvereageProductTransactions_Result> GetDailyAvereageProductTransactions()
//{
// var result = db.sp_Forecast_GetDailyAvereageProductTransactions();
// return result.ToList();
//}
//public List<sp_Forecast_GetDailyTimeSpecificAvereageProductTransactions_Result> GetDailyTimeSpecificAvereageProductTransactions()
//{
// var result = db.sp_Forecast_GetDailyTimeSpecificAvereageProductTransactions();
// return result.ToList();
//}
//public List<sp_Forecast_GetWeeklyAverageTransactions_Result> GetWeeklyAverageTransactions()
//{
// var result = db.sp_Forecast_GetWeeklyAverageTransactions();
// return result.ToList();
//}
//public List<sp_Forecast_GetWeeklyAvereageProductTransactions_Result> GetWeeklyAvereageProductTransactions()
//{
// var result = db.sp_Forecast_GetWeeklyAvereageProductTransactions();
// return result.ToList();
//}
//public List<sp_Forecast_GetProductCountYearDayByProductId_Result> GetProductCountYearDayByProductId(int productId)
//{
// var result = db.sp_Forecast_GetProductCountYearDayByProductId(productId);
// return result.ToList();
//}
//public List<sp_Forecast_GetProductCountMonthDayByProductId_Result> GetProductCountMonthDayByProductId(int productId)
//{
// var result = db.sp_Forecast_GetProductCountMonthDayByProductId(productId);
// return result.ToList();
//}
//public List<sp_Forecast_GetProductCountDayByProductId_Result> GetProductCountDayByProductId(int productId)
//{
// var result = db.sp_Forecast_GetProductCountDayByProductId(productId);
// return result.ToList();
//}
#endregion
#region R_Related
public ForecastResult ForecastByMethod(int branchId, int productId, string method, string dataType, int periods)
{
ForecastResult forecastResult = new ForecastResult();
//Methods method1 = (Methods)Enum.Parse(typeof(Methods), method, true);
DataPeriod datatype1 = (DataPeriod)Enum.Parse(typeof(DataPeriod), dataType, true);
//int productId = 1;
//Methods method = Methods.rwf; //meanf(YYMMDD,MMDD,MMWWDD,DD), rtw, rtw(with Drift), Moving AVG,ets, Arima, HoltWinters, msts
//DataPeriod dataType = DataPeriod.Daily;
//int periods = 50;
var values = GetCorrespondingDataByPeriod(datatype1, productId);
//FFCEntities db = new FFCEntities();
//var list = db.sp_Forecast_GetProductCountYearDayByProductId(productId).ToList();
//List<double> values = list.Select(r => Double.Parse(r.Count.ToString())).ToList();
//REngine.SetEnvironmentVariables(@"C:\Program Files\R\R-2.13.1\bin\i386");
//SetupPath();
//Log();
REngine.SetEnvironmentVariables();
// There are several options to initialize the engine, but by default the following suffice:
REngine engine = REngine.GetInstance();
//engine.Initialize();
// .NET Framework array to R vector.
//NumericVector testTs = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99, 1000 });
//NumericVector testTs = engine.CreateNumericVector(new double[] { 10, 20, 30, 40, 50 });
NumericVector data = engine.CreateNumericVector(values);
engine.SetSymbol("data", data);
//auto arima for monthly
engine.Evaluate("tsValue <- ts(data, frequency=160, start=c(2013.5))");
engine.Evaluate("library(forecast)");
engine.Evaluate(String.Format("Fit <- {0}(tsValue)", method.ToString())); // Fit <- Arima(tsValue)
//MethodManipulation(engine, method);
engine.Evaluate(String.Format("fcast <- forecast(Fit, h={0})", periods));
string image = PlotForecast(engine, method.ToString());
//var a = engine.Evaluate("fcast <- forecast(tsValue, h=5)").AsCharacter();
NumericVector forecasts = engine.Evaluate("fcast$mean").AsNumeric();
//NumericVector forecasts = engine.Evaluate("fcast$lower[,2]").AsNumeric();
forecastResult.BranchId = branchId;
forecastResult.ProductId = productId;
forecastResult.Method = db.Forecast_Methods.Where(r => r.ForecastIdentifier == method).Select(a => a.ForecastMethod).FirstOrDefault();
forecastResult.DatePeriod = datatype1.ToString();
forecastResult.ForecastPeriod = periods;
forecastResult.Values = forecasts.ToList();
forecastResult.ImagePath = "~/Content/Images/" + image;
//foreach (var item in forecasts)
//{
// Console.WriteLine(item);
//}
//engine.Dispose();
return(forecastResult);
}
