private void Predict()
{
double firstDay = context.DayStats.OrderByDescending(x => x.Date).Select(x => (double)x.Date.Day + 1).First();
int amountOfDays = 182;
var result = new LinReg[5];
var days = context.DayStats.Select(x => (double)x.Date.Day).ToArray();
Maths.LinearRegression(days,
context.DayStats.Select(x => (double)x.DAU).ToArray(),
out result[0].rSquared,
out result[0].yIntercept,
out result[0].Slope);
Maths.LinearRegression(days,
context.DayStats.Select(x => (double)x.NewUsers).ToArray(),
out result[1].rSquared,
out result[1].yIntercept,
out result[1].Slope);
Maths.LinearRegression(days,
context.DayStats.Select(x => (double)x.Revenue).ToArray(),
out result[2].rSquared,
out result[2].yIntercept,
out result[2].Slope);
Maths.LinearRegression(days,
context.ItemStatDays.GroupBy(x => x.Date).OrderBy(x => x.Key).Select(g => (double)g.Sum(p => p.Amount)).ToArray(),
out result[3].rSquared,
out result[3].yIntercept,
out result[3].Slope);
Maths.LinearRegression(days,
context.ItemStatDays.GroupBy(x => x.Date).OrderBy(x => x.Key).Select(g => (double)g.Sum(p => p.USD)).ToArray(),
out result[4].rSquared,
out result[4].yIntercept,
out result[4].Slope);
Prediction[] predictions = new Prediction[amountOfDays];
for (int i = 0; i < amountOfDays; i++)
{
predictions[i] = new Prediction
{
Date = new DateTime(2018, 1, 1).AddDays(firstDay + i - 1),
DAU = Convert.ToInt32((result[0].Slope * (firstDay + i)) + result[0].yIntercept),
NewUsers = Convert.ToInt32((result[1].Slope * (firstDay + i)) + result[1].yIntercept),
Revenue = Math.Round((result[2].Slope * (firstDay + i)) + result[2].yIntercept, 2),
SoldAmount = Convert.ToInt32((result[3].Slope * (firstDay + i)) + result[3].yIntercept),
SoldUSD = (result[4].Slope * (firstDay + i)) + result[4].yIntercept
};
Console.WriteLine("Day: {0} DAU: {1} NewUsers: {2} Revenue:{3} SoldAmount: {4} SoldUSD: {5}",
predictions[i].Date.ToShortDateString(), predictions[i].DAU, predictions[i].NewUsers, predictions[i].Revenue, predictions[i].SoldAmount,
predictions[i].SoldUSD);
}
context.Prediction.AddRange(predictions);
context.SaveChanges();
}
protected override void OnStateChange()
{
if (State == State.SetDefaults)
{
Description = @"TTMS momentum histogram with squeeze dots.";
Name = "TTMS";
Calculate = Calculate.OnPriceChange;
IsOverlay = false;
DisplayInDataBox = true;
DrawOnPricePanel = false;
DrawHorizontalGridLines = false;
DrawVerticalGridLines = false;
PaintPriceMarkers = true;
ScaleJustification = NinjaTrader.Gui.Chart.ScaleJustification.Right;
IsSuspendedWhileInactive = true;
MomentumLength = 20;
SqueezeLength = 20;
SqueezeDotBrush = Brushes.Red;
NormalDotBrush = Brushes.Blue;
HistAboveZeroRising = Brushes.Lime;
HistAboveZeroFalling = Brushes.DarkSlateGray;
HistBelowZeroFalling = Brushes.Red;
HistBelowZeroRising = Brushes.DarkSlateGray;
SoundAlertsOn = false;
BuySoundAlert = "Alert3.wav";
SellSoundAlert = "Alert4.wav";
AddPlot(new Stroke(Brushes.DarkSlateGray, 5), PlotStyle.Bar, "MomentumHistogram");
AddPlot(new Stroke(NormalDotBrush, 2), PlotStyle.Dot, "SqueezeDots");
}
else if (State == State.Configure)
{
lrm_ = new Series <double>(this);
medianPriceOsc_ = new Series <double>(this);
BB = Bollinger(2.0, SqueezeLength);
KC = KeltnerChannel(1.5, SqueezeLength);
DC = DonchianChannel(MomentumLength);
LR = LinReg(medianPriceOsc_, MomentumLength);
ema_ = EMA(MomentumLength);
}
}
