/// <summary>
/// Creates the PC plot given
/// </summary>
/// <param name="panel"></param>
/// <param name="filter"></param>
/// <param name="columnIndex">the column index for which we're clustering the data
/// in case we're using K-Means</param>
/// <param name="headers"></param>
/// <returns></returns>
private ParallelCoordinatesPlot InitializeParallelCoordinatesPlot(Panel panel,
IDataCubeProvider <float> filter, int columnIndex, List <string> headers)
{
ParallelCoordinatesPlot filterPlot = new ParallelCoordinatesPlot();
filterPlot.Input = filter;
filterPlot.Headers = headers;
// to color according to clusters
if (columnIndex != -1)
{
iColorMap.Index = columnIndex;
iDoc.iFilteredSelectedColorMap.Index = columnIndex;
}
filterPlot.ColorMap = iColorMap;
filterPlot.Enabled = true;
renderer.Add(filterPlot, panel);
return(filterPlot);
}
public TableLensEncapsulator(IDataCubeProvider data, ExcelDataProvider excelDataProvider)
{
this.excelDataProvider = excelDataProvider;
this.data = data;
// color map
colorMapForTableLens = new ColorMap();
colorMapForTableLens.AddColorMapPart(new LinearRgbColorMapPart(Color.Blue, Color.Red));
// transpos
List<int> selected = new List<int>();
selected.Add(SelectedIndex);
lensDataTransformer = new TransposDataTransformer();
lensDataTransformer.Input = this.data;
lensDataTransformer.SelectedCountry = selected;
lensDataTransformer.SelectedIndicator = SelectedIndicator;
lensDataTransformer.GetDataCube();
// table lens
tablelens = new TableLens();
lensDataTransformer.SelectedCountry = new List<int>(){0};
tablelens.Input = lensDataTransformer.GetDataCube();
colorMapForTableLens.Input = tablelens.Input;
tablelens.ColorMap = colorMapForTableLens;
List<string> countrylist = new List<string>();
countrylist.Add(excelDataProvider.RowIds[SelectedIndex]);
tablelens.HeadersList = countrylist;
}
