📄 polynomialfittingextended.aspx
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<%@ Page Language="VB" 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">
Sub Page_Load(sender As [Object], e As EventArgs)
' 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.PaletteName = Palette.Three
' The following line allows the source data from which the curve of best fits are
' calibrated to be plotted with curve of best fit and for the x-axis values to be
' syncronized.
'
ForecastChart.XAxis.Scale = Scale.Normal
'
'In the next four line we set the range of the axis
'
ForecastChart.XAxis.ScaleRange.ValueLow = 800
ForecastChart.XAxis.ScaleRange.ValueHigh = 1750
ForecastChart.YAxis.ScaleRange.ValueLow = 310
ForecastChart.YAxis.ScaleRange.ValueLow = 240
' The Forecast data
Dim de As New DataEngine()
de.ConnectionString = "Provider=Microsoft.Jet.OLEDB.4.0;data source=" + Server.MapPath("../../database/chartsample.mdb")
de.SqlStatement = "SELECT ID, Value FROM Statistics WHERE ID Between 1050 AND 1550"
de.DataFields = "xAxis=ID,yAxis=Value"
'Add a series
Dim scForecast As SeriesCollection = 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
Dim deviation As New Series()
Dim i As Integer
For i = 0 To (scForecast(0).Elements.Count) - 1
Dim el As New Element()
el.XValue = scForecast(0).Elements(i).XValue
el.YValue = 1E-10
deviation.Elements.Add(el)
Next i
' Declare a new serie for the ChiSquare elements
Dim chiSquareSeries As New Series()
' 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})
Dim generalLinear As New Series()
' In the next line we call the method which will find the best fitting curve
generalLinear = ForecastEngine.Advanced.GeneralLinear(scForecast(0), deviation, 800, 1750, 1)
generalLinear.Name = "0th Degree Polynomial"
generalLinear.Type = SeriesType.Spline
ForecastChart.SeriesCollection.Add(generalLinear)
' 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
Dim generalLinearModel3 As New Series()
' In the next line we call the method which will find the best fitting curve. The third and
' the forth parameter of this method represent the lower and upper limit on the XAxis
' between which the curve is represented
generalLinearModel3 = ForecastEngine.Advanced.GeneralLinear(scForecast(0), deviation, 800, 1750, 1)
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
Dim generalLinearModel4 As New Series()
generalLinearModel4 = ForecastEngine.Advanced.GeneralLinear(scForecast(0), deviation, 800, 1750, 1)
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
Dim generalLinearModel5 As New Series()
generalLinearModel5 = ForecastEngine.Advanced.GeneralLinear(scForecast(0), deviation, 800, 1750, 1)
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
Dim generalLinearModel6 As New Series()
generalLinearModel6 = ForecastEngine.Advanced.GeneralLinear(scForecast(0), deviation, 800, 1750, 1)
generalLinearModel6.Name = "5th Degree Polynomial"
generalLinearModel6.Type = SeriesType.Spline
ForecastChart.SeriesCollection.Add(generalLinearModel6)
End Sub 'Page_Load
</script>
</HEAD>
<BODY>
<DIV align="center">
<dotnet:Chart id="ForecastChart" runat="server"/>
</dotnet:Chart>
</DIV>
</BODY>
</HTML>
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