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<%@ Page Language="C#" Debug="true" Description="dotnetCHARTING Component" %>
<%@ Register TagPrefix="dotnet"  Namespace="dotnetCHARTING" Assembly="dotnetCHARTING"%>
<%@ Import Namespace="System.Drawing" %>
<%@ Import Namespace="System.Drawing.Drawing2D" %>
<%@ Import Namespace="dotnetCHARTING"%>
<HTML>
	<HEAD>
		<TITLE>.netCHARTING Forecasting Sample</TITLE>
		<script runat="server">

void Page_Load(Object sender,EventArgs e)
{
     
	// This sample demonstrates the use of GeneralLinear Forecasting engine in order to
	// find the function of best fit from three functions spaces. The data used for which
	// the fuctions are fit is a set of data which represents a FX exchange rate over a given
	// period of time. We index the period by the number of days after the inital date and the
	// eights function spaces are the spaces spanned by the following basis elements:
	//	
	// 1) {(1)}
	// 2) {(1), (x)}
	// 3) {(1), (x), (x^2)}
	// 4) {(1), (x), (x^2), (x^3)}
	// 5) {(1), (x), (x^2), (x^3), (x^4)}
	// 6) {(1), (x), (x^2), (x^3), (x^4), (x^5)}
	// 7) {(1), (x), (x^2), (x^3), (x^4), (x^5), (x^6)}
	// 8) {(1), (x), (x^2), (x^3), (x^4), (x^5), (x^6), (x^7)}
	//

	// The Forecast Chart
	ForecastChart.Title="Exchange";
	ForecastChart.TempDirectory="temp";
	ForecastChart.Debug=true;
	ForecastChart.Size = "1000x800";
	ForecastChart.LegendBox.Template ="%icon %name";
	
	ForecastChart.YAxis.ScaleRange.ValueLow = 220;
	ForecastChart.PaletteName = Palette.Three;
	
	// The Forecast data
	DataEngine de = new DataEngine ();
	de.ConnectionString = @"Provider=Microsoft.Jet.OLEDB.4.0;data source=" + Server.MapPath("../../database/chartsample.mdb");
	de.DateGrouping = TimeInterval.Days;
	de.StartDate = new DateTime(1983,3,10,0,0,0);
	de.EndDate = new DateTime(1984,12,10,23,59,59);
	de.SqlStatement= @"SELECT ID, Value AS q FROM Exchange WHERE Data >= #STARTDATE# AND Data <= #ENDDATE# ORDER BY Data ";

	//Add a series
	SeriesCollection scForecast = de.GetSeries ();
	ForecastChart.SeriesCollection.Add (scForecast);

	scForecast[0].Name = "Exchange";
	scForecast[0].Type = SeriesType.Spline;


	/*
	 * Takes off the marker off the line and spline series.
	 */
	ForecastChart.DefaultSeries.DefaultElement.Marker = new ElementMarker (ElementMarkerType.None);
	ForecastChart.ChartAreaLayout.Mode = ChartAreaLayoutMode.Vertical;
	
	// Generate a series of standard deviation for the given points
	Series deviation = new Series();
	for (int i = 0; i < scForecast[0].Elements.Count; i++ )
	{
		Element el = new Element();
		el.XValue = scForecast[0].Elements[i].XValue;
		el.YValue = 0.0000000001;
		deviation.Elements.Add(el);
	}
	
	// Note that this line is necessary in order to clear the function basis set by previous
	// example.
	//
	ForecastEngine.Options.Reset();
	
	// Set the first model function
	//
	// The second basis element: (1)
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{0});
	// Generate a new series which will draw the best fit line according with the model function which we just set
	Series generalLinear =  new Series();
	generalLinear = ForecastEngine.Advanced.GeneralLinear(scForecast[0], deviation);
	generalLinear.Name = "0th Degree Polynomial";
	generalLinear.Type = SeriesType.Spline;
	ForecastChart.SeriesCollection.Add(generalLinear);

	// Set the second model function ; we add x function to the basis functions
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{1});
	// Generate a new series which will draw the best fit line according with the model function which we just set
	Series generalLinearModel2 =  new Series();
	generalLinearModel2 = ForecastEngine.Advanced.GeneralLinear(scForecast[0], deviation);
	generalLinearModel2.Name = "1st Degree Polynomial";
	generalLinearModel2.Type = SeriesType.Spline;
	ForecastChart.SeriesCollection.Add(generalLinearModel2);

	// Set the third model function ; we add x^2 function to the basis functions
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{2});
	// Generate a new series which will draw the best fit line according with the model function which we just set
	Series generalLinearModel3 =  new Series();
	generalLinearModel3 = ForecastEngine.Advanced.GeneralLinear(scForecast[0], deviation);
	generalLinearModel3.Name = "2nd Degree Polynomial";
	generalLinearModel3.Type = SeriesType.Spline;
	ForecastChart.SeriesCollection.Add(generalLinearModel3);
	
	// We add x^3 function to the basis functions
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{3});
	// Generate a new series which will draw the best fit line according with the model function which we just set
	Series generalLinearModel4 =  new Series();
	generalLinearModel4 = ForecastEngine.Advanced.GeneralLinear(scForecast[0], deviation);
	generalLinearModel4.Name = "3rd Degree Polynomial";
	generalLinearModel4.Type = SeriesType.Spline;
	ForecastChart.SeriesCollection.Add(generalLinearModel4);
	
	// We add x^4 function to the basis functions
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{4});
	// Generate a new series which will draw the best fit line according with the model function which we just set
	Series generalLinearModel5 =  new Series();
	generalLinearModel5 = ForecastEngine.Advanced.GeneralLinear(scForecast[0], deviation);
	generalLinearModel5.Name = "4th Degree Polynomial";
	generalLinearModel5.Type = SeriesType.Spline;
	ForecastChart.SeriesCollection.Add(generalLinearModel5);

	// We add x^5 function to the basis functions
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{5});
	// Generate a new series which will draw the best fit line according with the model function which we just set
	Series generalLinearModel6 =  new Series();
	generalLinearModel6 = ForecastEngine.Advanced.GeneralLinear(scForecast[0], deviation);
	generalLinearModel6.Name = "5th Degree Polynomial";
	generalLinearModel6.Type = SeriesType.Spline;
	ForecastChart.SeriesCollection.Add(generalLinearModel6);

	// We add x^6 function to the basis functions
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{6});
	// Generate a new series which will draw the best fit line according with the model function which we just set
	Series generalLinearModel7 =  new Series();
	generalLinearModel7 = ForecastEngine.Advanced.GeneralLinear(scForecast[0], deviation);
	generalLinearModel7.Name = "6th Degree Polynomial";
	generalLinearModel7.Type = SeriesType.Spline;
	ForecastChart.SeriesCollection.Add(generalLinearModel7);

	// We add x^7 function to the basis functions
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{7});
	// Generate a new series which will draw the best fit line according with the model function which we just set
	Series generalLinearModel8 =  new Series();
	generalLinearModel8 = ForecastEngine.Advanced.GeneralLinear(scForecast[0], deviation);
	generalLinearModel8.Name = "7th Degree Polynomial";
	generalLinearModel8.Type = SeriesType.Spline;
	ForecastChart.SeriesCollection.Add(generalLinearModel8);

	// Fit the 27th Degree Polynomial
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{8});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{9});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{10});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{11});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{12});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{13});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{14});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{15});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{16});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{17});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{18});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{19});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{20});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{21});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{22});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{23});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{24});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{25});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{26});
	ForecastEngine.Options.AddSumOfPowerTerms(new double[]{1}, new double[]{27});
	// Generate a new series which will draw the function of best from the fnuctoin spacce available.
	Series generalLinearModel9 =  new Series();
	generalLinearModel9 = ForecastEngine.Advanced.GeneralLinear(scForecast[0], deviation);
	generalLinearModel9.Name = "27th Degree Polynomial";
	generalLinearModel9.DefaultElement.Color = Color.FromArgb(0,0,0);
	generalLinearModel9.Type = SeriesType.Spline;
	ForecastChart.SeriesCollection.Add(generalLinearModel9);

}

		</script>
	</HEAD>
	<BODY>
		<DIV align="center">
			
			<dotnet:Chart id="ForecastChart" runat="server"/>
			</dotnet:Chart>
			
		</DIV>
	</BODY>
</HTML>
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