/// <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; }