private static imbSCI.Core.math.range.matrix.HeatMapModel PublishMatrix(ILogBuilder log, folderNode folder, string name_selected, List <WeightDictionary> sfs) { imbSCI.Core.math.range.matrix.HeatMapModel model = sfs.GetHeatMapMatrix(); model.DetectMinMax(); model.GetDataTable(name_selected, "Overlaping terms and their frequencies").GetReportAndSave(folder, null, name_selected); try { HeatMapRender heatMapRender = new HeatMapRender(); heatMapRender.style.accronimLength = 3; heatMapRender.style.BaseColor = Color.Black; heatMapRender.style.fieldHeight = 50; heatMapRender.style.fieldWidth = 50; heatMapRender.RenderAndSave(model, folder.pathFor(name_selected, imbSCI.Data.enums.getWritableFileMode.overwrite, "Heat map showing overlaping terms and their frequencies")); } catch (Exception ex) { log.log(ex.Message); } return(model); }
public override ExperimentDataSetFoldContextPair <OperationContext> Execute(ILogBuilder logger, OperationContext executionContextMain = null, ExperimentModelExecutionContext executionContextExtra = null) { ExperimentDataSetFoldContextPair <OperationContext> output = new ExperimentDataSetFoldContextPair <OperationContext>(fold, executionContextMain); Open(); output.context.DeployDataSet(fold, logger); entityOperation.TextRendering(output.context, notes, requirements.MayUseTextRender); corpusOperation.SpaceModelPopulation(output.context, notes); corpusOperation.SpaceModelCategories(output.context, notes); FeatureFilterAndWeightModelAnalysis fwmAnalysis = new FeatureFilterAndWeightModelAnalysis(output.context.spaceModel, setup.WeightModels, setup.FilterModels); corpusOperation.FeatureSelection(output.context, notes); corpusOperation.VectorSpaceConstruction(output.context, notes, true); corpusOperation.FeatureVectorConstruction(output.context, notes); fwmAnalysis.ExecuteAnalysis(output.context, logger, fold_notes.folder_feature); //if (setup.tasks.HasFlag(CWPAnalysisReportsEnum.reportTermDistribution)) //{ // var model = output.context.spaceModel.categories.GetHeatMapMatrix(); // HeatMapRender heatMapRender = new HeatMapRender(); // heatMapRender.RenderAndSave(model, fold_notes.folder_feature.pathFor("category_overlap_beforeFS", imbSCI.Data.enums.getWritableFileMode.overwrite, "Heat map showing overlaping terms and their frequencies, before feature selection")); //} if (setup.tasks.HasFlag(CWPAnalysisReportsEnum.reportDatasetStructure)) { DatasetStructureReport datasetStructureReport = DatasetStructureReport.MakeStructureReport(fold, fold.name); datasetStructureReport.Compute(); datasetStructureReport.Publish(fold_notes.folder, true, true, true); } if (setup.tasks.HasFlag(CWPAnalysisReportsEnum.reportDatasetMetrics)) { ContentAnalytics contentAnalytics = new ContentAnalytics(fold_notes.folder_entity); var Metrics = contentAnalytics.ProduceMetrics(fold.name, fold, output.context, logger); Metrics.ReportHTMLTags(fold_notes.folder_entity, fold.name); Metrics.ReportSample(fold_notes.folder_entity, fold.name, 1000); Metrics.ReportTokens(fold_notes.folder_corpus, fold.name, 1000); Metrics.GetDataTable(fold_notes.name).GetReportAndSave(fold_notes.folder_entity, null, "Dataset"); } if (setup.tasks.HasFlag(CWPAnalysisReportsEnum.reportTermDistribution)) { imbSCI.Core.math.range.matrix.HeatMapModel model = output.context.spaceModel.categories.GetHeatMapMatrix(); model.GetDataTable("CategoryFreqOverlap", "Overlaping terms and their frequencies").GetReportAndSave(fold_notes.folder, null, "CategoryOverlap"); try { HeatMapRender heatMapRender = new HeatMapRender(); heatMapRender.style.accronimLength = 3; heatMapRender.style.BaseColor = Color.Black; heatMapRender.style.fieldHeight = 50; heatMapRender.style.fieldWidth = 50; var svg = heatMapRender.Render(model); svg.Save(fold_notes.folder_feature.pathFor("category_overlap_afterFS.svg", imbSCI.Data.enums.getWritableFileMode.overwrite, "Heat map showing overlaping terms and their frequencies")); svg.SaveJPEG(fold_notes.folder_feature.pathFor("category_overlap_afterFS.jpg", imbSCI.Data.enums.getWritableFileMode.overwrite, "Heat map showing overlaping terms and their frequencies")); } catch (Exception ex) { logger.log(ex.Message); } List <histogramModel> models = new List <histogramModel>(); foreach (var cat in output.context.spaceModel.categories) { var hist = cat.GetHistogram(20); models.Add(hist); DataTable dt_hist = hist.GetDataTableForFrequencies(); dt_hist.GetReportAndSave(fold_notes.folder, null, "histogram_table_" + cat.name); string h_p = fold_notes.folder_feature.pathFor(cat.name + "_term_distribution.svg", imbSCI.Data.enums.getWritableFileMode.overwrite, "Histogram with term distribution for category [" + cat.name + "]"); // File.WriteAllText(h_p, hist.GetSVGChart()); } models.BlendHistogramModels(fold.name).GetReportAndSave(fold_notes.folder, null, "histogram_all"); } if (setup.tasks.HasFlag(CWPAnalysisReportsEnum.reportCWPAnalytics)) { analysis.Prepare(output.context.spaceModel, logger); analysis.Analysis(fold_notes); } Close(); return(output); }