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);
}
