public void GenerateOverlapMatrixes(ILogBuilder log, folderNode folder)
{
List <histogramModel> histograms = new List <histogramModel>();
foreach (Int32 atSize in FSTests.Get1stKeys())
{
ConcurrentDictionary <string, FeatureSelectionAnalysis> concurrentDictionary = FSTests[atSize];
String prefix = concurrentDictionary.Keys.toCsvInLine() + "_" + atSize;
GenerateOverlapMatrixes(prefix, concurrentDictionary, log, folder);
List <histogramModel> models = new List <histogramModel>();
foreach (var selcol in concurrentDictionary.Values)
{
//histogramModel model = new histogramModel(50, "SelectedDistributionAt" + atSize);
var freq = selcol.weightedFeatures.index.Values.OrderByDescending(x => x.weight);
histogramModel model = histogramModelExtensions.GetHistogramModel(freq, "Weights", x => x.weight, 20);
models.Add(model);
}
models.BlendHistogramModels(prefix).GetReportAndSave(folder, null, "histogram" + prefix);
}
}
/// <summary>
/// Gets the SVG histogram.
/// </summary>
/// <param name="model">The histogram model</param>
/// <param name="is3D">if set to <c>true</c> it will be 3D</param>
/// <param name="depth">The depth.</param>
/// <returns></returns>
public static String GetSVGHistogram(this histogramModel model, Boolean is3D = false, short depth = 10)
{
if (!is3D)
{
HistogramChart output = new HistogramChart(500, 360, model.targetBins);
XmlDocument xml = output.GenerateChart(model.GetDataTableForFrequencies(), histogramModel.DEFAULT_COLUMN_NAME, histogramModel.DEFAULT_COLUMN_VALUE);
return(xml.OuterXml);
}
else
{
Histogram3DChart output = new Histogram3DChart(500, 360, model.targetBins, depth);
XmlDocument xml = output.GenerateChart(model.GetDataTableForFrequencies(), histogramModel.DEFAULT_COLUMN_NAME, histogramModel.DEFAULT_COLUMN_VALUE);
return(xml.OuterXml);
}
}
public static histogramModel GetHistogram(this SpaceDocumentModel dictionary, Int32 binCount = 50)
{
histogramModel model = dictionary.terms.GetRankedTokenFrequency().GetHistogramModel(dictionary.name, x => x.Value, binCount); //new histogramModel(binCount, dictionary.name);
return(model);
}
public static histogramModel GetHistogram(this WeightDictionary dictionary, Int32 binCount = 50)
{
histogramModel model = dictionary.index.Values.ToList().GetHistogramModel(dictionary.name, x => x.weight, binCount); //new histogramModel(binCount, dictionary.name);
return(model);
}
