public IPlaneContext ExecutePlaneMethod(IPlaneContext inputContext, ExperimentModelExecutionContext generalContext, ILogBuilder logger)
{
//if (generalContext == null)
//{
// generalContext = new PlanesMethodContext();
//}
IEntityPlaneContext entityInputContext = inputContext as IEntityPlaneContext;
ICorpusPlaneContext entityContext = EntityMethod.ExecutePlaneMethod(inputContext, generalContext, logger) as ICorpusPlaneContext;
IVectorPlaneContext corpusContext = CorpusMethod.ExecutePlaneMethod(entityContext, generalContext, logger) as IVectorPlaneContext;
IFeaturePlaneContext vectorContext = VectorMethod.ExecutePlaneMethod(corpusContext, generalContext, logger) as IFeaturePlaneContext;
IFeaturePlaneContext featureContext = FeatureMethod.ExecutePlaneMethod(vectorContext, generalContext, logger) as IFeaturePlaneContext;
// --- the results reporting
var evaluationMetrics = generalContext.truthTable.EvaluateTestResultsToMetricSet(featureContext.testResults, generalContext.runName + "-" + notes.folder.name, logger);
DataTableTypeExtended <classificationEval> inclassEvalTable = new DataTableTypeExtended <classificationEval>("inclass_evaluation", "Test results, per class");
evaluationMetrics.GetAllEntries().ForEach(x => inclassEvalTable.AddRow(x));
inclassEvalTable.AddRow(evaluationMetrics.GetSummary("Sum"));
notes.SaveDataTable(inclassEvalTable, notes.folder_classification);
classificationReport averagedReport = new classificationReport(evaluationMetrics, generalContext.averagingMethod);
averagedReport.Classifier = FeatureMethod.classifier.name;
averagedReport.saveObjectToXML(notes.folder_classification.pathFor(averagedReport.Name + ".xml", imbSCI.Data.enums.getWritableFileMode.overwrite, "Serialized classification evaluation results summary"));
generalContext.testSummaries.Add(averagedReport);
averagedReport.ReportToLog(notes);
featureContext.provider.Dispose();
EntityMethod.CacheProvider.Dispose();
return(generalContext);
}
/// <summary>
/// Generates feature vectors
/// </summary>
/// <param name="inputContext">The input context - related to this plane.</param>
/// <param name="generalContext">General execution context, attached to the <see cref="T:imbNLP.Toolkit.Planes.PlanesMethodDesign" /></param>
/// <param name="logger">The logger.</param>
/// <returns>
/// Retur
/// </returns>
public IPlaneContext ExecutePlaneMethod(IPlaneContext inputContext, ExperimentModelExecutionContext generalContext, ILogBuilder logger)
{
notes.logStartPhase("[3] Vector Plane - execution", "");
IVectorPlaneContext context = (IVectorPlaneContext)inputContext;
FeaturePlaneContext finalContext = new FeaturePlaneContext();
finalContext.provider.StoreAndReceive(context);
ICorpusPlaneContext corpusContext = finalContext.provider.GetContext <CorpusPlaneContext>();
// deploying feature vector space constructor
featureSpaceConstructor.Deploy(constructorSettings, context.vectorSpace);
featureSpaceConstructor.Deploy(constructorSettings, corpusContext.SelectedFeatures);
Dictionary <string, FeatureVector> docByName = new Dictionary <string, FeatureVector>();
notes.log(":: Constructing feature vectors");
// constructing the feature vectors
foreach (IVector vector in context.vectorSpace.documents)
{
var fv = featureSpaceConstructor.ConstructFeatureVector(vector);
docByName.Add(fv.name, fv);
finalContext.featureSpace.documents.Add(fv);
}
foreach (var link in context.LabelToDocumentLinks.links)
{
finalContext.featureSpace.labelToDocumentAssociations.Add(docByName[link.NodeB.name], link.NodeA, 1);
}
if (generalContext.reportOptions.HasFlag(PlanesReportOptions.report_featureVectors))
{
var dt = finalContext.featureSpace.MakeTable(featureSpaceConstructor, "FeatureSpace", "Feature space");
notes.SaveDataTable(dt, notes.folder_feature);
}
notes.logEndPhase();
return(finalContext);
}
/// <summary>
/// Executes the plane method, invoking contained functions according to the settings
/// </summary>
/// <param name="inputContext">The input context - related to this plane.</param>
/// <param name="generalContext">General execution context, attached to the <see cref="T:imbNLP.Toolkit.Planes.PlanesMethodDesign" /></param>
/// <param name="logger">The logger.</param>
/// <returns>
/// Retur
/// </returns>
public IPlaneContext ExecutePlaneMethod(IPlaneContext inputContext, ExperimentModelExecutionContext generalContext, ILogBuilder logger)
{
notes.logStartPhase("[2] Corpus Plane - execution", "");
ICorpusPlaneContext context = (ICorpusPlaneContext)inputContext;
VectorPlaneContext outputContext = new VectorPlaneContext();
outputContext.provider.StoreAndReceive(context);
context.stemmContext = new StemmingContext(stemmer);
Dictionary <String, SpaceDocumentModel> documentVsModel = new Dictionary <string, SpaceDocumentModel>();
// modelling the documents
foreach (TextDocument doc in context.corpus_documents)
{
SpaceDocumentModel model = spaceConstructor.ConstructDocument(doc.content, doc.name, context.space, context.stemmContext, tokenizer);
List <SpaceLabel> labels = spaceConstructor.GetLabels(doc.labels, context.space);
Boolean isUnknownLabel = true;
foreach (SpaceLabel label in labels)
{
if (label.name != SpaceLabel.UNKNOWN)
{
isUnknownLabel = false;
}
context.space.LabelToDocumentLinks.Add(label, model, 1);
}
context.space.documents.Add(model);
if (!isUnknownLabel)
{
context.space.terms.MergeDictionary(model.terms);
}
documentVsModel.Add(doc.name, model);
}
if (generalContext.reportOptions.HasFlag(PlanesReportOptions.report_fold_textrender))
{
foreach (TextDocument doc in context.corpus_documents)
{
String prefix = doc.labels.FirstOrDefault();
if (prefix.isNullOrEmpty())
{
prefix = SpaceLabel.UNKNOWN;
}
String fn = prefix + "_" + doc.name;
String pth = notes.folder_entity.pathFor(fn.getFilename("txt"), imbSCI.Data.enums.getWritableFileMode.overwrite, "Textual representation of website [" + doc.name + "], produced by rendering and blending settings", true);
doc.content.saveStringToFile(pth, imbSCI.Data.enums.getWritableFileMode.overwrite);
}
}
if (generalContext.reportOptions.HasFlag(PlanesReportOptions.report_fold_stats))
{
foreach (WebSiteDocumentsSet ds in context.dataset)
{
DataTable dt = ds.MakeTable(documentVsModel);
notes.SaveDataTable(dt, notes.folder_entity);
}
var dt_vsm = context.space.LabelToDocumentLinks.MakeTable("LabelToDocument", "Relationships between labels and documents in the primary Vector Space Model");
notes.SaveDataTable(dt_vsm, notes.folder_corpus);
}
if (generalContext.reportOptions.HasFlag(PlanesReportOptions.report_corpusDictionary))
{
notes.SaveDataTable(context.space.terms.MakeTable("corpus_stats", "Training set dictionary, after stemming", generalContext.DictionaryReportLimit), notes.folder_corpus);
}
#region SELECTING THE FEATURES
// forming corpus global weight
context.SelectedFeatures = new WeightDictionary();
List <KeyValuePair <string, double> > filter_result = filter.SelectFeatures(context.space);
List <string> FV = new List <string>();
FV.AddRange(filter_result.Select(x => x.Key));
if (filter_result.Any())
{
foreach (var pair in filter_result)
{
context.SelectedFeatures.AddEntry(pair.Key, pair.Value);
}
if (generalContext.reportOptions.HasFlag(PlanesReportOptions.report_selectedFeatures))
{
notes.SaveDataTable(context.SelectedFeatures.MakeTable("selected_features", "Features selected for BoW construction", new List <string>()
{
filter.function.shortName
}, generalContext.DictionaryReportLimit), notes.folder_corpus);
}
}
else
{
logger.log("-- Feature selection function returned zero set. All features [" + context.space.terms.Count + "] are therefore accepted as selected.");
var tkns = context.space.terms.GetTokens();
foreach (var tkn in tkns)
{
context.SelectedFeatures.AddEntry(tkn, 1);
}
}
#endregion
notes.log("Selected features [" + context.SelectedFeatures.entries.Count + "] by [" + filter.functionSettings.functionName + "]");
//context.space =
//weightModel.Deploy();
outputContext.vectorSpace = new Vectors.VectorSpace();
foreach (SpaceLabel label in context.space.labels)
{
var docs = context.space.LabelToDocumentLinks.GetAllLinked(label);
if (label.name != SpaceLabel.UNKNOWN)
{
SpaceCategoryModel categoryModel = new SpaceCategoryModel(label, docs);
context.space.LabelToCategoryLinks.Add(label, categoryModel, 1);
context.space.categories.Add(categoryModel);
notes.log("Class [" + categoryModel.name + "] BoW model created - terms[" + categoryModel.terms.Count + "] ");
}
}
outputContext.LabelToDocumentLinks = context.space.LabelToDocumentLinks;
// preparing the model
weightModel.PrepareTheModel(context.space);
// logger.log(":: Creating VectorSpace instances for documents");
// building document VSM
foreach (SpaceDocumentModel docModel in context.space.documents)
{
var wd = weightModel.GetWeights(FV, docModel, context.space);
VectorDocument docVec = new VectorDocument(docModel.name);
docVec.terms = wd;
if (generalContext.reportOptions.HasFlag(PlanesReportOptions.report_documentBoWModels))
{
DataTable dt = wd.MakeTable("docVec_" + docModel.name, "Document vector model", null, 10000);
notes.SaveDataTable(dt, notes.folder_vector);
}
outputContext.vectorSpace.documents.Add(docVec);
}
// logger.log(":: Creating VectorSpace instances for categories");
// building category VSM
foreach (SpaceCategoryModel catModel in context.space.categories)
{
var wd = weightModel.GetWeights(FV, catModel, context.space);
VectorLabel catVec = new VectorLabel(catModel.name);
catVec.terms = wd;
if (generalContext.reportOptions.HasFlag(PlanesReportOptions.report_documentBoWModels))
{
DataTable dt = wd.MakeTable("catVec_" + catModel.name, "Document vector model", null, 10000);
notes.SaveDataTable(dt, notes.folder_vector);
}
outputContext.vectorSpace.labels.Add(catVec);
}
if (generalContext.reportOptions.HasFlag(PlanesReportOptions.report_documentBoWModels))
{
foreach (SpaceCategoryModel catModel in context.space.categories)
{
var dt = catModel.terms.MakeTable("cat_" + catModel.name, "Vector Space BoW weighted model, representing a category");
notes.SaveDataTable(dt, notes.folder_vector);
}
}
notes.logEndPhase();
return(outputContext);
}
