/// <summary>
/// Should forcast using 12 months data, falling back to 6 month if unavailable
/// //ForcastSlope = _ForcastVals[0];
//ForcastIntercept = _ForcastVals[1];
//ForcastValue = _ForcastVals[2];
//ForcastRangeUpperBount = _ForcastVals[3];
/// </summary>
/// <param name="SKUID"></param>
private double[] Forcast(int SkuId, DateTime EndDate)
{
StatusMonContext db = new StatusMonContext();
List <double> SalesData;
double[] xdata;
double[] ydata;
DateTime EndDate12 = EndDate.AddMonths(-12);
DateTime EndDate6 = EndDate.AddMonths(-6);
int date = (EndDate.Date.Year * 12 + EndDate.Date.Month);
//Test if 12 Month of Data Exists
if (db.SalesOrderDetails.Where(o => o.SalesOrder.OrderDate <= EndDate12).Count() > 0)
{
SalesData = MonthlySalesD(SkuId, EndDate.AddMonths(-11), EndDate);
xdata = new double[] { date - 11, date - 10, date - 9, date - 8, date - 7, date - 6, date - 5, date - 4, date - 3, date - 2, date - 1, date };
//12 Months!
}
else if (db.SalesOrderDetails.Where(o => o.SalesOrder.OrderDate.Date <= EndDate6).Count() > 0)
{
//6 Months
SalesData = MonthlySalesD(SkuId, EndDate.AddMonths(-5), EndDate);
xdata = new double[] { date - 5, date - 4, date - 3, date - 2, date - 1, date }; //Actual Values are nominal
}
else
{
//Not enough Data to forcast accurately
db.Dispose();
return(new double[] { 0, 0, 0, 0 });
}
db.Dispose();
ydata = SalesData.ToArray();
return(Linear.Forcast(date + 1, xdata, ydata));
}
static void Main(string[] args)
{
//new List<double> {0.0, 0.0, 0.0, 0.0};
double[] yValues = new double[] { 0, 1, 1, 0, 1, 0 };
double[] xValues = new double[] { 8, 7, 6, 5, 4, 3 };
double xValueToPredict = 9;
double[] t = Linear.Forcast(xValueToPredict, xValues, yValues);
System.Console.WriteLine(t[2]);
System.Console.ReadLine();
System.Console.WriteLine((DateTime.Now.Date.Year * 12 * DateTime.Now.Date.Month));
System.Console.ReadLine();
}
public static void GenerateSingleLinearForcast(int id)
{
ApplicationDbContext db = new ApplicationDbContext();
MonthlyTotal MT = db.MonthlyTotals.Where(p => p.SKU == id).OrderBy(g => g.Date).ToArray().Last();
DateTime ForcastDate = MT.Date.AddMonths(1);
int forcast_month_id = (12 * ForcastDate.Year) + ForcastDate.Month;
List <MonthlyTotal> Totals = db.MonthlyTotals.Where(P => P.SKU == id && P.Date < ForcastDate).OrderByDescending(O => O.Date).Take(12).ToList();
List <LinearDataSet> DS = new List <LinearDataSet>();
double Intercept = 0;
double Slope = 0;
double Absolute_Quantity_Forcast = 0;
double Quantity_Forcast = 0;
string JSON_MonthlyTotals = JsonConvert.SerializeObject(DS.ToArray());
int Sample_Size = Totals.Count();
string SkuClass = "Unknown";
bool Valid = false;
if (Sample_Size > 3)
{
Valid = true;
double[] YTotals = Totals.Select(P => P.Absolute_Quantity_Sold).ToArray();
double[] YTotalsR = Totals.Select(P => P.Quantity_Sold).ToArray();
double[] XMonth = Totals.Select(P => (double)(P.Date.Year * 12) + P.Date.Month).ToArray();
double[] t = Linear.Forcast(forcast_month_id, XMonth, YTotals);
DS.Add(new LinearDataSet()
{
label = "Actual Sales", y = YTotalsR, x = XMonth
});
DS.Add(new LinearDataSet()
{
label = "Adjusted Sales", y = YTotals, x = XMonth
});
List <double> TrendYVals = new List <double>();
List <double> TrendYValsSeasonal = new List <double>();
foreach (double x in XMonth)
{
double val = x * t[1] + t[0];
TrendYVals.Add(val);
}
DS.Add(new LinearDataSet()
{
label = "Trend Sales",
y = TrendYVals.ToArray(),
x = XMonth
});
JSON_MonthlyTotals = JsonConvert.SerializeObject(DS.ToArray());
Intercept = t[0];
Slope = t[1];
Absolute_Quantity_Forcast = t[2];
Quantity_Forcast = MonthlyTotal.AddSeasonality(Absolute_Quantity_Forcast, ForcastDate.Month);
SkuClass = SingleLinearForcast.GetSkuClass((int)Totals.Select(P => P.Quantity_Sold).ToArray().Sum());
}
SingleLinearForcast Forcast = new SingleLinearForcast()
{
SKU = id,
Month_Id = (12 * ForcastDate.Year) + ForcastDate.Month, //Month * Year
Date = ForcastDate, //Forcasted Date
Quantity_Forcast = Quantity_Forcast,
Absolute_Quantity_Forcast = Absolute_Quantity_Forcast,
Slope = Slope,
Intercept = Intercept,
JSON_MonthlyTotals = JSON_MonthlyTotals,
Sample_Size = Sample_Size,
SkuClass = SkuClass,
Valid = Valid,
};
db.SingleLinearForcasts.Add(Forcast);
db.SaveChanges();
}